Path Finding Visualization vs Art of Stat

Want to see various pathfinding algorithms in action? With Path Finding Visualization, you can visualize, in action, six different algorithms. This app allows you to select your own starting and ending points, select the algorithm you want to use, and add walls in order to create boundaries. This app includes the following algorithms: Dijkstra's - Works by expanding outwards until it reaches the target node. Guaranteed to find the shortest path as long as there are not any negative weights. Bidirectional Dijkstra's - Dijkstra's algorithm from both sides. A* - Like Dijkstra's in that it favors nodes close to the starting point, but also favors nodes close to the ending point (heuristic). It does not guarantee the shortest path. A tie-breaker that prefers straight lines was included in order to prevent multiple nodes from having the same F values. Bidirectional A* - The A* algorithm from both sides. Breadth-First Search - Traverses through a graph one level at a time until it finds the target node. Since there are no weights, this algorithm does guarantee the shortest path. Depth-First Search - Traverses through a graph by going as deep as possible and then backtracking until it finds the target node. It does not guarantee the shortest path. Learning about or want to visualize any of the above algorithms in action? Download Path Finding Visualization today and have a better understanding of how each algorithm works.

Explore the Central Limit Theorem, learn about the correlation coefficient and linear regression, and visualize the coverage probability of confidence intervals or Type I & II Errors in hypothesis testing. Build understanding by experiencing these important concepts step-by-step. For students and teachers of statistics. The Art of Stat: Concepts app provides access to the following modules: - Central Limit Theorem for Means - Central Limit Theorem for Proportions - Explore Correlation - Explore Linear Regression - Explore Coverage - Errors & Power CLT: Select from several real population distributions (left and right-skewed or fairly symmetric) and simulate taking a sample from the population. Visualize how the sampling distribution builds, step-by-step. Explore the effect on the sampling distribution as you increase the sample size. Overlay the normal distribution. Compare the sampling distribution of the mean to the population distribution, both visually and in terms of key statistics. Explore Correlation/Linear Regression: Create (and delete) points in a scatterplot by tabbing on the screen. Show the regression line or residuals. Simulate scatterplots and guess the correlation coefficient. Coverage and Errors: Explore what 95% coverage for a confidence interval for a population mean or proportion implies. See the Type I and Type II error and explore how they depend on the sample size and the true parameter value. Find and visualize the power of a hypothesis test.